The human brain is the most intelligent thing that we know of. One of the best prospects for developing true artificial intelligence is to reverse-engineer the brain. Reverse-engineering the brain will involve imaging the brain down to every detail, modelling it, and simulating it. There is already a lot of research going on to reverse-engineer the brain from fields like neuroscience, computer science, engineering, and pyschology. We are not able to image the brain at the neuronal level of detail yet, but broad simulations of different brain regions have already been created. Understanding the brain is something scientists have worked at for a long time and we will soon be approaching a time when we can not only understand it, but replicate it.

The biggest current restriction on reverse-engineering the brain is our current imaging technology. Both the spatial and temporal resolution of our best imaging now (MRI) are not good enough to capture individual firings of individual neurons. Still, we are able to get general ideas of which groups of neurons are firing when and what they do, so that much progress has been made in simulating various brain regions. But as our imaging systems get better then we should be able to capture and record every neuronal firing in the brain and develop a complete model of its workings.

The brain is much different from a computer and building a full model of it will provide us with many benefits. The brain’s neurons fire very slowly compared to a computer, but they are huge numbers of neurons and they are all connected in a massively parallel way, providing us with great pattern recognition abilites. The brain is able to rewire itself and grow new neuronal connections to learn new skills and memories. By combining these features with the great speed and perfect memory of a computer, we will develop an incredible artificial intelligence.

There are a number of current projects going on to reverse-engineer parts of the brain. Many of the pattern recognition algorithms used in the field of artificial intelligence and data mining such as neural networks and Bayesian networks were developed from theories of how the brain worked. Researchers have developed detailed models of the cerebellum and parts of the visual cortex. Lloyd Watts at MIT has developed a model of the auditory pathway in the brain that was better at differentiating a voice from a crowd than any program written before.

Current people are working on reverse-engineering the brain from the sensory inputs inward, since the senses are something we can understand easily. As we develop accruate models of the pathways the sensory data follow, we will develop models further in the brain, where the information is combined and stored and decisions are made. Along with the rapidly improving imaging technology, a complete model of the brain will soon become reality.